Pyrochar has been identified as a favorable soil conditioner that can effectively ameliorate soil acidification. Hydrochar is considered a more affordable carbon material than pyrochar, but its effect on the process of soil acidification has yet to be investigated. An indoor incubation and a soil column experiment were conducted to study the effect of rice straw hydrochar application on nitrification and NO₃⁻-N leaching in acidic red soil. Compared to the control and pyrochar treatments, respectively, hydrochar addition mitigated the net nitrification rate by 3.75–48.75% and 57.92–78.19%, in the early stage of urea fertilization. This occurred mainly because a greater amount of dissolved organic carbon (DOC) was released from hydrochar than the other treatments, which stimulated microbial nitrogen immobilization. The abundances of ammonia-oxidizing archaea and ammonia-oxidizing bacteria were dramatically elevated by 25.62–153.19% and 12.38–22.39%, respectively, in the hydrochar treatments because of DOC-driven stimulation. The cumulative leaching loss of NO₃⁻-N in soils amended with hydrochar was markedly reduced by 43.78–59.91% and 61.70–72.82% compared with that in the control and pyrochar treatments, respectively, because hydrochar promoted the soil water holding capacity by 2.70–9.04% and reduced the residual NO₃⁻-N content. Hydrochar application can dramatically diminish total H⁺ production from soil nitrification and NO₃⁻-N leaching. Thus, it could be considered an economical soil amendment for ameliorating soil acidification.

Diminishing soil fertility and crop productivity due to traditional intensive cultivation has prompted the use of straw and manure to improve soil health in Northeast China. However, few comparative studies have explored the influence of varying straw and manure incorporation depths on crop growth. A field experiment in the rainfed black soil regions of Gongzhuling and Keshan assessed the effects of deep (30 cm) and shallow (15 cm) incorporations of straw and manure on soil fertility, maize root growth, and maize productivity. Deep incorporations, via subsoiling tillage (DST) and deep-plow (DDT) tillage, enhanced soil water storage of 30–100 cm soil layer during periods of low rainfall, improved the availability of nutrients (nitrogen, phosphorus, and potassium) and soil organic matter content, especially in deeper soil, compared to shallow incorporation using rotary tillage (SRT). Both DST and DDT induced a larger rooting depth and a higher fine root (diameter class 0–0.5 mm) length density by 31.0% and 28.9%, respectively, accompanied by reduced root turnover. Furthermore, the sub-surface foraging strategies of roots under the DST and DDT treatments boosted the total nitrogen, phosphorus, and potassium uptake (6.5–17.9%) and achieved a higher dry mass accumulation during the later growth period, thus leading to notable improvements in the 100-kernel weight and yield (16.1–19.7%) and enhancing water- and nutrient-use efficiencies by 2.5–20.5%. Overall, compared to shallow incorporation, deep incorporation of straw and manure significantly enhances root growth and spatial distribution of soil water and nutrients, which has great potential for increasing maize yield in rainfed agricultural areas.

Rapid and cost-effective estimation of soil total nitrogen (TN) is essential for soil fertility assessment and nutrient management. However, the performance of laboratory visible–near-infrared (Vis–NIR) models is shaped not only by preprocessing and modeling strategy but also by sample preparation and the soil’s compositional background. In this study, TN prediction was evaluated using 376 topsoil samples from two contrasting datasets: Mollisols from the black-soil region of Northeast China and Ultisols from Qiyang County, Hunan Province, southern China. Spectra acquired over 350–2500 nm for three particle-size fractions were preprocessed using Savitzky–Golay smoothing combined with standard normal variate (SNV), first-derivative, or second-derivative transformations, and modeled using partial least squares regression (PLSR), support vector regression (SVR), and extreme gradient boosting (XGBoost). Model development used a 5 × 5 nested cross-validation followed by evaluation on a sample-grouped held-out test set. Among all combinations, XGBoost with first-derivative preprocessing on the 0.25 mm fraction produced the best performance, with test R² values of 0.91 for Mollisol and 0.78 for Ultisol. Shapley additive explanations (SHAP) and principal component analysis (PCA) consistently identified informative spectral regions at 430–480 and 1330–1450 nm for Mollisol and at 585–635, 820–900, and 2180–2240 nm for Ultisol. Prediction errors were larger in the sampled Ultisol dataset and increased with DCB-extractable Fe and mineral backgrounds. A second-stage log-domain residual correction incorporating ancillary soil properties further reduced the Ultisol RMSE from 0.30 to 0.27 g kg⁻¹. These findings support the 0.25 mm, first-derivative, XGBoost workflow as a robust laboratory Vis–NIR approach for TN prediction and indicate that composition-aware residual correction can improve prediction in oxide- and mineral-rich soils.

Crop rotation and microbial driving force significantly influence soil phosphorus (P) bioavailability and crop yield. However, differences in underlying microbial mechanisms in rotations remain unclear. We examined rice yield, P uptake, soil and microbial P contents, enzyme activity, and P functional genes over six years (2016–2022) to elucidate microbial mechanisms driving rice yield in rice–wheat (RW) and rice–oilseed rape (RO) rotations. RO significantly increased rice yield and plant P uptake by 9.17% and 20.70%, respectively, compared to RW. Soil total (TP) and available (AP) P contents were significantly lower (4.83% and 18.31%, respectively) under RO than RW, whereas microbial biomass phosphorus (MBP) and acid phosphatase activity (EP) were greater (39.40% and 128.45%, respectively). PICRUSt2 results revealed that RO increased phoA phoB (alkaline phosphatase), phnX (phosphonoacetaldehyde hydrolase [EC:3.11.1.1]), gcd (Quinoprotein glucose dehydrogenase [EC:1.1.5.2]), and ppaC (manganese-dependent inorganic pyrophosphatase) and decreased phnD (phosphonate transport system substrate-binding protein), ugpE (sn-glycerol 3-phosphate transport system permease protein), ugpA (sn-glycerol 3-phosphate transport system permease protein), and phnO ((aminoalkyl)phosphonate N-acetyltransferase [EC:2.3.1.280]) abundance. Random forest analysis showed that ppaC, phnD, gcd, and phnX were important for rice yield and plant P uptake. Partial least squares analysis revealed that RO indirectly increased rice yield by influencing MBP and affecting plant P uptake through P functional genes. Overall, RO improves rice yield and P bioavailability by altering P functional genes (ppaC, phnD, gcd, and phnX), providing new perspectives on crop–microorganism interactions and resource use efficiency.